Data processing method, device, equipment and storage medium

Abstract

The embodiments of the present application relate to a data processing method, device, equipment and storage medium. The method includes: obtaining facial information of active criminals in the target area within the detection period; wherein, active criminals are people with a history of stealing vehicles; obtaining behavioral data of target active criminals entering and leaving a specific place during the detection period based on the facial information of active criminals and the snapshot data of people entering and leaving a specific place during the detection period; when the target active criminal is determined to be a suspicious person involved in vehicle theft based on the behavioral data, the information of the target active criminal is sent to the user terminal. The method focuses on analyzing active criminals with a history of vehicle theft, warns suspicious persons of vehicle theft, and realizes the transformation of the case investigation idea from "from case to person" to "from person to case", thereby greatly improving the efficiency of vehicle theft case investigation and reducing the incidence of vehicle theft cases.

Description

Technical Field

[0001] The present application relates to the field of Internet applications, and in particular to a data processing method, apparatus, device and storage medium. Background Art

[0002] In traditional technology, after a theft occurs, investigators retrieve video data from the area around the theft location and analyze the video data frame by frame based on the time reported by the owner to identify the suspect. However, with limited police resources at the grassroots level, police resources often become a bottleneck in the investigation of such cases, seriously affecting the efficiency of the investigation of theft cases. Summary of the invention

[0003] Based on this, it is necessary to provide a data processing method, device, equipment and storage medium to address the technical problem of low efficiency in detecting theft cases using traditional methods.

[0004] In a first aspect, an embodiment of the present application provides a data processing method, including:

[0005] Obtaining facial information of active criminals in the target area during the detection period; wherein the active criminals are those who have a history of vehicle theft and have activity tracks in the target area during the detection period;

[0006] According to the facial information of the active criminal and the captured data of the persons entering and leaving the specific place during the detection period, the behavior data of the target active criminal entering and leaving the specific place during the detection period is obtained; wherein the specific place is located in the target area;

[0007] When it is determined according to the behavior data that the target person with an active criminal record is a suspicious person involved in vehicle theft, information of the target person with an active criminal record is sent to a user terminal.

[0008] In a second aspect, an embodiment of the present application provides a data processing device, including:

[0009] The first acquisition module is used to acquire the facial information of active criminals in the target area within the detection period; wherein the active criminals are people who have a history of stealing vehicles and have activity tracks in the target area within the detection period;

[0010] A second acquisition module is used to acquire the behavior data of the target active criminal record person who enters and leaves the specific place during the detection period according to the facial information of the active criminal record person and the captured data of the person who enters and leaves the specific place during the detection period; wherein the specific place is located in the target area;

[0011] The sending module is used to send the information of the target active criminal record to the user terminal when it is determined that the target active criminal record person is a suspicious person involved in vehicle theft according to the behavior data.

[0012] In a third aspect, an embodiment of the present application provides a data processing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the data processing method provided in the first aspect of the embodiment of the present application are implemented.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the data processing method provided in the first aspect of the embodiment of the present application are implemented.

[0014] The technical solution provided in the embodiment of the present application obtains the behavioral data of the target active criminals who enter and exit the specific place during the detection period based on the facial information of the active criminals in the target area during the detection period and the captured data of the people who enter and exit the specific place during the detection period, and when the target active criminal is determined to be a suspicious person involved in vehicle theft based on the behavioral data, the information of the target active criminal is sent to the user terminal to remind the case handlers to conduct a key investigation on the target active criminal. This technical solution conducts a key analysis of active criminals with a history of vehicle theft, warns suspicious persons of vehicle theft, and realizes the transformation of the case investigation idea from "from case to person" to "from person to case", thereby greatly improving the efficiency of vehicle theft case investigation and reducing the incidence of vehicle theft cases. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flowchart of a data processing method provided in an embodiment of the present application;

[0016] Figure 2 Another flowchart of the data processing method provided in the embodiment of the present application;

[0017] Figure 3 A schematic diagram of a process for determining active criminals provided in an embodiment of the present application;

[0018] Figure 4 A schematic diagram of a process for sending information of a target active criminal record person provided in an embodiment of the present application;

[0019] Figure 5 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application;

[0020] Figure 6 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present application more clear, the technical solution in the embodiments of the present application is further described in detail through the following embodiments and in combination with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

[0022] It should be noted that the execution subject of the following method embodiment may be a data processing device, which may be implemented as part or all of the data processing device through software, hardware, or a combination of software and hardware. Optionally, the data processing device may be a mobile terminal or a server. The mobile terminal may be any one of a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (such as a vehicle navigation terminal), and a mobile phone, and the server may be an independent server or a server cluster composed of multiple servers. The following method embodiment is described by taking the execution subject as a data processing device as an example.

[0023] Figure 1 A flow chart of a data processing method provided in an embodiment of the present application. Figure 1 As shown, the method may include:

[0024] S101. Acquire facial information of active criminals in a target area within a detection period.

[0025] The target area can be understood as the geographical scope for vehicle theft analysis, and the target area can be divided by administrative regions, such as the whole country, province, city, district / county, and township. Of course, the target area can also be divided by community. In practical applications, the target area can be set according to actual needs. The detection period can be understood as the time domain scope for vehicle theft analysis, and the granularity of the division can be month, week, day, and hour, etc. It can also be set accordingly based on actual needs, such as setting the detection period to one week, etc. Optionally, the vehicle can be an electric car, a motorcycle, or a bicycle.

[0026] The above-mentioned active criminals are those who have a history of stealing vehicles and have activity tracks in the target area during the detection period. Usually, vehicle theft cases are mostly committed by habitual offenders and repeat offenders. Therefore, we can focus on the whereabouts of criminals with activity tracks in the target area during the detection period, and identify suspicious persons involved in vehicle theft cases by analyzing their whereabouts. In actual applications, the database of the public security system stores the ID information of criminals with vehicle theft cases. Therefore, the data processing equipment can obtain the ID information of active criminals in the target area during the detection period from the historical cases stored in the database, and extract the facial information of active criminals from the ID information.

[0027] S102, obtaining the behavior data of the target active criminal who enters and leaves the specific place during the detection period based on the facial information of the active criminal and the captured data of the persons who enter and leave the specific place during the detection period.

[0028] The specific place is located in the target area, and the specific place can be a vehicle sales point, such as a second-hand car trading market. The target active criminal record person refers to the active criminal record person who enters and exits the specific place during the detection period. Usually, monitoring equipment (such as cameras) are installed at the entrance and exit and inside the specific place. The monitoring equipment can take pictures of people and vehicles entering and leaving the specific place to form captured data.

[0029] After acquiring the facial information of the active ex-offender, the data processing device can match the facial information of the active ex-offender with the captured data of the persons entering and leaving the specific place during the detection period to determine whether the active ex-offender appears in the specific place during the detection period. If a match is found, it can be determined that the active ex-offender appears in the specific place during the detection period, and the active ex-offender who appears in the specific place is determined as the target active ex-offender. At the same time, the behavioral data of the target active ex-offender is acquired based on the matched target captured data. Optionally, the behavioral data may include information such as facial expressions and behavioral behaviors.

[0030] The specific process of the above matching can be: extracting the first facial features of the person with active criminal record from the facial information of the person with active criminal record, and extracting the second facial features of the person in the captured data (wherein the facial features can be facial features and face shape features), calculating the feature similarity between the first facial features and the second facial features, and if the feature similarity exceeds a preset threshold, it is determined that the facial information of the person with active criminal record is matched in the captured data.

[0031] S103: When it is determined according to the behavior data that the target person with an active criminal record is a suspicious person involved in vehicle theft, information of the target person with an active criminal record is sent to a user terminal.

[0032] Since the target active criminal has entered and exited a specific place during the detection period, it is necessary to focus on analyzing the whereabouts of the target active criminal. After obtaining the behavior data of the target active criminal, it can be determined whether the target active criminal is a suspicious person involved in vehicle theft based on the behavior data. If so, the information of the target active criminal is sent to the user terminal. For example, the information of the target active criminal is sent to the user terminal held by the case handler in the target area.

[0033] Taking the behavioral data including facial expressions and behaviors as an example, when the target active criminal has a tense facial expression and behaves furtively, it can be determined that the target active criminal is a suspicious person involved in vehicle theft.

[0034] The data processing method provided in the embodiment of the present application obtains the behavior data of the target active criminals who enter and exit the specific place during the detection period based on the facial information of the active criminals in the target area during the detection period and the captured data of the people who enter and exit the specific place during the detection period, and when it is determined that the target active criminal is a suspicious person involved in vehicle theft based on the behavior data, the information of the target active criminal is sent to the user terminal to remind the case handlers to conduct a key investigation on the target active criminal. This technical solution conducts a key analysis of active criminals with a history of vehicle theft, and warns suspicious persons of vehicle theft in advance, realizing the transformation of the case investigation idea from "from case to person" to "from person to case", thereby greatly improving the efficiency of vehicle theft case investigation and reducing the incidence of vehicle theft cases.

[0035] In one embodiment, optionally, the behavioral data of the above-mentioned target active criminal may include the number of times appearing in a specific place, the riding status when entering and leaving the specific place, and the attribute characteristics of the vehicle ridden when there is a vehicle being ridden. Among them, the attribute characteristics of the vehicle may include the model, color, and shape of the headlights. Based on this, the following embodiment also provides another data processing method. It should be noted that the following S202-S203 is an optional implementation of the above-mentioned S102, and the following S204-S206 is an optional implementation of the above-mentioned S103. Figure 2 As shown, the method may include:

[0036] S201. Obtain facial information of active criminals in the target area within a detection period.

[0037] S202: Match the facial information of the active criminal with the captured data of persons entering and leaving the specific place during the detection period to obtain the number of appearances of the target active criminal at the specific place during the detection period.

[0038] The data processing device can match the facial information of the active criminal with the captured data of the person entering and leaving the specific place during the detection period. If a match is found, it can be determined that the active criminal appeared in the specific place during the detection period, and the active criminal who appeared in the specific place is determined as the target active criminal, and the matched target captured data is archived into the activity track record of the target active criminal. After all the captured data in the detection period are processed, the number of target captured data stored in the activity track record of the target active criminal is counted, and the number is determined as the number of appearances of the target active criminal in the specific place.

[0039] S203, performing scene snapshot image structured analysis on the matched target snapshot data to obtain the riding status of the target active criminal record person each time when entering and exiting the specific place and the attribute characteristics of the vehicle ridden by the target active criminal record person if there is a riding vehicle.

[0040] In order to obtain deeper key information, the matched target snapshot data can be subjected to scene snapshot image structured analysis, that is, the target object in the target snapshot data can be structured and the text semantic description can be performed, including pedestrian structured, vehicle structured, and person-bicycle structured. Among them, person-bicycle structured is to perform structured processing and identification of pedestrians riding bicycles in the target snapshot data, including structured processing of the cyclist's clothing, vehicle characteristics, etc. By performing scene snapshot image structured analysis on the target snapshot data, it is possible to obtain whether the target active criminal record person rides a vehicle every time he enters and exits a specific place, and if there is a vehicle, the vehicle attribute characteristics such as the model, color, and shape of the headlights of the vehicle ridden by the target active criminal record person can be obtained.

[0041] For example, assuming that the target active criminal record appears in a specific place 5 times during the detection period, after performing scene capture image structured analysis on the target capture data, it can be found that the target active criminal record did not ride a vehicle when entering and exiting the specific place for the first two times, rode a vehicle when entering the specific place for the next three times, and did not ride a vehicle when leaving the specific place. Moreover, the vehicle attributes such as the model, color, and shape of the headlights of the vehicles ridden when entering the specific place for the next three times were different.

[0042] S204. When the number of occurrences is greater than or equal to a preset number of occurrences, the number of times the target active criminal has ridden under preset conditions is determined according to the riding status of the target active criminal each time he enters and exits the specific place.

[0043] Wherein, the preset condition is that there is a vehicle when entering the specific place, and there is no vehicle when leaving the specific place. In actual application, the preset number of occurrences can be set accordingly based on actual business needs.

[0044] After obtaining the behavior data of the target active criminal record person, determine whether the number of appearances of the target active criminal record person in a specific place during the detection period is greater than or equal to the preset number of appearances. If so, determine the number of rides of the target active criminal record person under the preset conditions based on the riding status of the target active criminal record person each time he enters and exits the specific place. If not, analyze the whereabouts of the next target active criminal record person in the specific place. Among them, the riding status is used to indicate whether the target active criminal record person has ridden a vehicle.

[0045] Continuing with the example in S203 above, assume that the target active criminal has appeared 5 times in a specific place during the detection period, and assume that the preset number of appearances is 2 times. Since the target active criminal has appeared more than the preset number of appearances in a specific place, the number of rides of the target active criminal under the preset conditions can be further determined based on the riding status of the target active criminal each time the target active criminal enters and exits the specific place. Since the target active criminal did not ride a vehicle during the first two times of entering and exiting the specific place, the target active criminal rode a vehicle during the last three times of entering the specific place and did not ride a vehicle when leaving the specific place. Therefore, it can be determined that the target active criminal rode 3 times under the preset conditions.

[0046] S205. If the riding times are greater than or equal to the preset riding times, determine whether the attribute characteristics of the vehicle ridden by the target active criminal each time are the same.

[0047] The preset riding times is less than or equal to the preset occurrence times. Similarly, in practical applications, the preset riding times can be set accordingly based on actual business needs.

[0048] After obtaining the number of rides of the target active criminal under the preset conditions, it is determined whether the number of rides is greater than or equal to the preset number of rides. If so, it is further determined whether the vehicle attributes such as the model, color, and light shape of the vehicle ridden by the target active criminal are the same each time. If they are the same, the whereabouts of the next target active criminal in a specific place are analyzed; if they are not the same, the following S206 is executed.

[0049] S206: Determine that the target person with an active criminal record is a suspicious person involved in vehicle theft, and send information about the target person with an active criminal record to a user terminal.

[0050] In this embodiment, the scene snapshot image structured analysis is performed on the matched target snapshot data to extract deeper key information, such as the number of times the target active criminal record person appears in a specific place, the riding state when entering and exiting the specific place each time, and the vehicle attribute characteristics such as the model, color, and light shape of the vehicle ridden by the target person when there is a vehicle. At the same time, combined with the number of times the target active criminal record person appears in a specific place, the riding state when entering and exiting the specific place each time, and the vehicle attribute characteristics such as the model, color, and light shape of the vehicle ridden by the target person when there is a vehicle, it is determined whether the target active criminal record person is a suspicious person involved in vehicle theft. By performing judgment analysis on deeper behavioral data, the accuracy of the analysis results is improved, thereby improving the accuracy of the early warning.

[0051] In one embodiment, a specific process for determining active criminals in a target area within a detection period is also provided. Based on the above embodiment, optionally, as Figure 3 As shown, before the above S101, the method may further include:

[0052] S301. Obtain information on all persons with criminal records involved in vehicle theft cases.

[0053] Usually, vehicle theft cases are mostly committed by habitual offenders and repeat offenders, so it is possible to focus on all persons with criminal records involved in vehicle theft cases. In practical applications, the database of the public security system stores information on persons with criminal records of vehicle theft cases, so the data processing device can obtain information on all persons with criminal records involved in vehicle theft cases from historical cases stored in the database.

[0054] S302: Obtain an information set of active personnel.

[0055] The activity track data of people in the target area during the detection period are comprehensively collected, including transportation ticket purchase information, travel accommodation information, Internet cafe registration information, and medical clinic registration information, etc. The activity tracks of the above-mentioned people in the target area are drawn out in chronological order and stored in the activity track data set.

[0056] S303 , matching the information of each criminal with the active person information set respectively, to determine the active criminals in the target area within the detection period.

[0057] Among them, active criminals refer to criminals with criminal records who have activity tracks in the target area during the detection period. After obtaining the information of all criminals with criminal records involved in vehicle theft cases and the active personnel information set, the information of each criminal with criminal records is matched with the active personnel information set to screen out criminals with activity tracks in the target area during the detection period, that is, active criminals. Subsequently, the whereabouts of these active criminals are analyzed in detail to screen out suspicious persons involved in vehicle theft.

[0058] After the suspicious person involved in the vehicle theft is determined, in order to improve the efficiency of catching the suspicious person, based on the above embodiment, optionally, as follows Figure 4 As shown, the process of sending the information of the target active criminal record person to the user terminal may include:

[0059] S401, obtaining the activity track of the target active criminal.

[0060] After determining that the target active criminal record person is a suspicious person involved in vehicle theft, the activity track of the target active criminal record person is obtained from the active person information set.

[0061] S402: Determine, based on the activity trajectory, target addresses where the target active criminal often appears.

[0062] After obtaining the activity track of the target active criminal, the target address where the target active criminal frequently appears can be determined by analyzing the activity track. For example, based on the time in the activity track, the place where the target active criminal appears at night can be determined as the usual residence of the target active criminal. In this way, when the data processing device sends the personal information of the target active criminal to the user terminal, the target address where the target active criminal frequently appears can also be sent to the user terminal held by the case handler, so as to achieve the accurate capture of the target active criminal.

[0063] S403: Send the personal information of the target active criminal and the target address to the user terminal held by the case handler.

[0064] In this embodiment, by matching the information of all criminals involved in vehicle theft cases with the active personnel information set, the active criminals in the target area within the detection period are determined, and the activity tracks of active criminals are focused on, which reduces redundant data, narrows the analysis scope of vehicle theft cases, and further improves the efficiency of theft case investigation. At the same time, after determining that the target active criminal is a suspicious person involved in vehicle theft, the personal information of the target active criminal and the frequently appearing target address are sent to the user terminal held by the case handler, so as to achieve the accurate capture of the target active criminal, and prevent the occurrence of vehicle theft cases in advance.

[0065] Figure 5 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application. Figure 5 As shown, the device may include: a first acquisition module 501, a second acquisition module 502 and a sending module 503.

[0066] Specifically, the first acquisition module 501 is used to acquire the facial information of active criminals in the target area within the detection period; wherein the active criminals are people who have a history of vehicle theft and have activity tracks in the target area within the detection period;

[0067] The second acquisition module 502 is used to acquire the behavior data of the target active criminal record person who enters and leaves the specific place during the detection period according to the facial information of the active criminal record person and the captured data of the person who enters and leaves the specific place during the detection period; wherein the specific place is located in the target area;

[0068] The sending module 503 is used to send the information of the target active criminal record to the user terminal when it is determined that the target active criminal record person is a suspicious person involved in vehicle theft according to the behavior data.

[0069] The data processing device provided in the embodiment of the present application obtains the behavior data of the target active criminals who enter and exit the specific place during the detection period based on the facial information of the active criminals in the target area during the detection period and the captured data of the people who enter and exit the specific place during the detection period, and when it is determined that the target active criminal is a suspicious person involved in vehicle theft based on the behavior data, the information of the target active criminal is sent to the user terminal to remind the case handlers to conduct a key investigation on the target active criminal. This technical solution conducts a key analysis of active criminals with a history of vehicle theft, warns suspicious persons of vehicle theft, and realizes the transformation of the case investigation idea from "from case to person" to "from person to case", thereby greatly improving the efficiency of vehicle theft case investigation and reducing the incidence of vehicle theft cases.

[0070] Optionally, the behavior data includes the number of times the person appears at the specific place, the riding status when entering and exiting the specific place, and the attribute characteristics of the vehicle ridden if there is a vehicle being ridden.

[0071] On the basis of the above embodiment, optionally, the second acquisition module 502 is specifically used to match the facial information of the active criminal with the captured data of people entering and leaving the specific place during the detection period, so as to obtain the number of occurrences of the target active criminal at the specific place during the detection period; perform scene capture picture structured analysis on the matched target captured data, so as to obtain the riding status of the target active criminal each time the target active criminal enters and leaves the specific place and the attribute characteristics of the vehicle ridden by the target active criminal if there is a riding vehicle.

[0072] Based on the above embodiment, optionally, the device further includes: an analysis module.

[0073] Specifically, the analysis module is used to determine the number of times the target active criminal has ridden under preset conditions according to the riding status of the target active criminal each time entering and exiting the specific place when the number of appearances is greater than or equal to the preset number of appearances; if the number of rides is greater than or equal to the preset number of rides, determine whether the attribute characteristics of the vehicle ridden by the target active criminal each time are the same; if they are not the same, determine that the target active criminal is a suspicious person involved in vehicle theft; wherein the preset conditions are that there is a riding vehicle when entering the specific place and there is no riding vehicle when leaving the specific place; the preset number of rides is less than or equal to the preset number of appearances.

[0074] On the basis of the above embodiment, optionally, the device further includes: a third acquisition module, a fourth acquisition module, and a processing module.

[0075] Specifically, the third acquisition module is used to acquire information of all criminals involved in the vehicle theft case before the first acquisition module 501 acquires facial information of active criminals in the target area within the detection period;

[0076] The fourth acquisition module is used to acquire an active person information set; wherein the active person information set stores information about persons with activity tracks in the target area within the detection period;

[0077] The processing module is used to match the information of each criminal with the active person information set to determine the active criminals in the target area within the detection period.

[0078] Based on the above embodiment, optionally, the sending module 503 is specifically used to obtain the activity trajectory of the target active criminal record person; determine the target address where the target active criminal record person often appears based on the activity trajectory; and send the personal information of the target active criminal record person and the target address to the user terminal held by the case handler.

[0079] Optionally, the vehicle includes an electric vehicle, a motorcycle or a bicycle.

[0080] In one embodiment, a data processing device is provided, and its structural diagram can be as follows: Figure 6 As shown. The device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the device is used to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the device is used to store data involved in the data processing process. The network interface of the device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data processing method is implemented.

[0081] Those skilled in the art will understand that Figure 6 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the device to which the scheme of the present application is applied. The specific device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0082] In one embodiment, a data processing device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0083] Obtaining facial information of active criminals in the target area during the detection period; wherein the active criminals are those who have a history of vehicle theft and have activity tracks in the target area during the detection period;

[0084] According to the facial information of the active criminal and the captured data of the persons entering and leaving the specific place during the detection period, the behavior data of the target active criminal entering and leaving the specific place during the detection period is obtained; wherein the specific place is located in the target area;

[0085] When it is determined according to the behavior data that the target person with an active criminal record is a suspicious person involved in vehicle theft, information of the target person with an active criminal record is sent to a user terminal.

[0086] Optionally, the behavior data includes the number of times the person appears at the specific place, the riding status when entering and exiting the specific place, and the attribute characteristics of the vehicle ridden if there is a vehicle being ridden.

[0087] In one embodiment, when the processor executes the computer program, the following steps are also implemented: matching the facial information of the active criminal with the captured data of people entering and leaving the specific place during the detection period to obtain the number of occurrences of the target active criminal at the specific place during the detection period; performing scene capture picture structured analysis on the matched target captured data to obtain the riding status of the target active criminal each time the target active criminal enters and leaves the specific place and the attribute characteristics of the vehicle ridden by the target active criminal if there is a riding vehicle.

[0088] In one embodiment, the processor also implements the following steps when executing the computer program: when the number of occurrences is greater than or equal to the preset number of occurrences, determining the number of times the target active criminal has ridden under preset conditions based on the riding status of the target active criminal each time entering and exiting the specific place; if the number of rides is greater than or equal to the preset number of rides, determining whether the attribute characteristics of the vehicle ridden by the target active criminal each time are the same; if they are not the same, determining that the target active criminal is a suspicious person involved in vehicle theft; wherein the preset condition is that there is a riding vehicle when entering the specific place and there is no riding vehicle when leaving the specific place; the preset number of rides is less than or equal to the preset number of occurrences.

[0089] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining information of all persons with criminal records involved in the vehicle theft case; obtaining an active person information set; matching the information of each person with criminal records with the active person information set respectively to determine active persons with criminal records in the target area within the detection period; wherein the active person information set stores information of persons with activity tracks in the target area within the detection period.

[0090] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the activity trajectory of the target active criminal; determining the target address where the target active criminal frequently appears based on the activity trajectory; and sending the personal information of the target active criminal and the target address to the user terminal held by the case handler.

[0091] Optionally, the vehicle includes an electric vehicle, a motorcycle or a bicycle.

[0092] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0093] Obtaining facial information of active criminals in the target area during the detection period; wherein the active criminals are those who have a history of vehicle theft and have activity tracks in the target area during the detection period;

[0094] According to the facial information of the active criminal and the captured data of the persons entering and leaving the specific place during the detection period, the behavior data of the target active criminal entering and leaving the specific place during the detection period is obtained; wherein the specific place is located in the target area;

[0095] When it is determined according to the behavior data that the target person with an active criminal record is a suspicious person involved in vehicle theft, information of the target person with an active criminal record is sent to a user terminal.

[0096] The data processing apparatus, device and storage medium provided in the above embodiments can execute the data processing method provided in any embodiment of the present application, and have the corresponding functional modules and beneficial effects of executing the method. For technical details not described in detail in the above embodiments, please refer to the data processing method provided in any embodiment of the present application.

[0097] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0098] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0099] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A data processing method, characterized in that: include: Obtain information on all persons with a history of vehicle theft from the public security system's database; Acquire the information set of active personnel based on the transportation ticket purchase information, travel accommodation information, Internet cafe registration information, and medical clinic registration information of personnel in the target area during the detection period; The active person information set includes information about persons with activity tracks in the target area during the detection period; Matching the information of each criminal with the active person information set to determine the active criminals in the target area during the detection period; wherein the active criminals are those who have a history of vehicle theft and have activity tracks in the target area during the detection period; Obtaining the ID information of the active criminal from a database of the public security system, and extracting the facial information of the active criminal from the ID information; Based on the facial information of the active criminal and the captured data of the persons entering and leaving the specific place during the detection period, the behavior data of the target active criminal entering and leaving the specific place during the detection period is obtained; wherein the specific place is located in the target area and is related to vehicle theft, and the behavior data includes the number of times the person appears in the specific place, the riding status when entering and leaving the specific place, and the attribute characteristics of the vehicle ridden when there is a riding vehicle; When it is determined according to the behavior data that the target person with an active criminal record is a suspicious person involved in vehicle theft, information of the target person with an active criminal record is sent to a user terminal.

2. The method according to claim 1, characterized in that: The step of obtaining the behavior data of the target person with active criminal record who enters and exits the specific place during the detection period based on the facial information of the person with active criminal record and the captured data of the person who enters and exits the specific place during the detection period includes: Matching the facial information of the active criminal with the captured data of people entering and leaving the specific place during the detection period to obtain the number of appearances of the target active criminal at the specific place during the detection period; The matched target snapshot data is subjected to scene snapshot image structured analysis to obtain the riding status of the target active criminal record person each time he enters and exits the specific place and the attribute characteristics of the vehicle ridden by the target active criminal record person if there is a riding vehicle.

3. The method according to claim 1, characterized in that Determining the target active criminal as a suspicious person involved in vehicle theft based on the behavior data includes: When the number of appearances in the specific place is greater than or equal to the preset number of appearances, the number of rides of the target active criminal record person under the preset condition is determined according to the riding status of the target active criminal record person each time when entering and leaving the specific place; wherein the preset condition is that there is a riding vehicle when entering the specific place and there is no riding vehicle when leaving the specific place; If the riding number is greater than or equal to the preset riding number, determining whether the attribute characteristics of the vehicle ridden by the target active criminal record person each time are the same; wherein the preset riding number is less than or equal to the preset occurrence number; If they are not the same, the target active criminal is determined to be a suspected person involved in vehicle theft.

4. The method according to any one of claims 1 to 3, characterized in that The sending the information of the target active criminal record person to the user terminal includes: Obtain the activity track of the target active criminal; Determine, based on the activity trajectory, target addresses where the target active criminal offender frequently appears; The personal information of the target active criminal and the target address are sent to the user terminal held by the case handling personnel.

5. The method according to any one of claims 1 to 3, characterized in that The vehicle includes an electric vehicle, a motorcycle or a bicycle.

6. A data processing device, characterized in that: include: The third acquisition module is used to obtain information of all persons with a criminal record of vehicle theft from the database of the public security system; The fourth acquisition module is used to obtain the activity personnel information set according to the transportation ticket purchase information, travel accommodation information, Internet cafe registration information and medical clinic registration information of the personnel in the target area during the detection period; The active person information set includes information about persons with activity tracks in the target area during the detection period; A processing module, used for matching the information of each person with a criminal record with the active person information set to determine the active person with a criminal record in the target area within the detection period; wherein the active person with a criminal record is a person who has a history of stealing vehicles and has an activity track in the target area within the detection period; A first acquisition module is used to obtain the certificate information of the active criminal record person from the database of the public security system, and extract the face information of the active criminal record person from the certificate information; A second acquisition module is used to acquire the behavior data of the target active criminal with a criminal record who enters and exits the specific place during the detection period based on the facial information of the active criminal with a criminal record and the captured data of the person who enters and exits the specific place during the detection period; wherein the specific place is located in the target area and is related to vehicle theft, and the behavior data includes the number of times the person appears in the specific place, the riding status when entering and exiting the specific place, and the attribute characteristics of the vehicle ridden when there is a riding vehicle; The sending module is used to send the information of the target active criminal record to the user terminal when it is determined that the target active criminal record person is a suspicious person involved in vehicle theft according to the behavior data.

7. A data processing device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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